Telemetry is the measurement and transmission of data that is often collected at remote or inaccessible locations and transmitted to local sites, often for the purpose of real-time monitoring. Telemetry is used in various fields including, for example, space exploration, oil drilling, flight testing, missile testing, and meteorology. In many situations, the presence of a human observer at the point of data collection is not feasible, but real-time access to the data for analysis and decision-making may be necessary.
The extent to which data can be provided at a sufficient rate for real-time applications depends in part on how much data can be transmitted in a given bandwidth of the telemetry system. Data compression is one way in which the amount of data transmitted in a particular time interval can be decreased. The principle of data compression is to reduce redundancy in a data set by efficient representation of intrinsic correlation in the data. Compression technologies can be divided into two categories: lossless and lossy. Lossless compression allows the exact original data to be reconstructed from the compressed data, while lossy compression cannot reconstruct data identical to the original, although a substantial amount of data can remain to satisfy the need of a given application.
When compressing data, the higher the compression ratio, the higher the potential rate of data transfer. However, data compression usually involves a trade-off between high compression ratio and resources (e.g., time, computing power, and power consumption). In real-time applications, in which the time between generation of data and the processing and receipt of the data should be as small as possible, computation complexity and delay costs often cannot be tolerated. Further limitations are imposed when lossless compression is desired. Lossless compression usually achieves a lower compression ratio as compared to lossy compression. Nevertheless, a low-delay, low-complexity, but high-ratio lossless compression of data is sometimes desirable for some real-time telemetry systems. Known compression algorithms, such as the Lempel-Ziv algorithm or Huffman coding, can be used to compress telemetry data, but these compression algorithms can not be used in realtime compression because entire data set needs be explored to build dictionary during the compression. Furthermore, their computational complexity and delay costs may not be tolerable in real-time applications.
The disclosed systems and methods are directed to overcoming one or more of the shortcomings set forth above and/or other shortcomings of the prior art.